Both hyperlipidemic acute pancreatitis and fatty liver disease are associated with lipid metabolism disorders and are commonly comorbid with each other in clinical practice. The pathogenesis of such comorbidity involves the interaction between multiple factors such as hypertriglyceridemia， metabolic syndrome， obesity， and insulin resistance， and these factors may form a vicious cycle and jointly promote disease progression. In clinical practice， hyperlipidemic acute pancreatitis is characterized by severe disease conditions， a high incidence rate of complications， a high mortality rate， and a tendency for recurrence， and it can easily lead to multi-organ damage and even multiple organ failure without timely treatment， posing a serious threat to the life of patients. Starting from the various signaling pathways associated with hyperlipidemic acute pancreatitis comorbid with fatty liver disease， this article discusses the potential molecular mechanisms of synergistic pathogenesis between hyperlipidemic acute pancreatitis and fatty liver disease， so as to provide a reference for the early prevention and treatment of such comorbidity.

Background/Aims: Acetyl coenzyme A (acetyl-CoA) is one of the most essential metabolites in cell metabolism but its function and concentration in hepatocellular carcinoma (HCC) remain elusive and controversial. Methods: A comprehensive analysis of acetyl-CoA levels and acetyl-CoA synthetase 2 (ACSS2) expression across a range of samples, including patient specimens from both hepatitis B virus (HBV) positive and HBV negative HCC individuals, HBV-transgenic mouse HCC models, and multiple cell lines. Furthermore, to evaluate the functional significance of ACSS2 in HBV-related HCC, we implemented both genetic and pharmacological inhibition strategies targeting ACSS2. Molecular mechanism and mitophagy assessment were revealed by cleavage under target and tagmentation sequencing, RNA sequencing, bioinformatic analyses, transmission electron microscopy and JC-1 staining. Results: Our study revealed a distinct metabolic signature of HBV-related HCC, marked by elevated acetyl-CoA, which was driven by ACSS2. ACSS2 was upregulated by the carbohydrate response element-binding protein in HBV-related HCC. Furthermore, ACSS2 improved tumor cell proliferation, an effect that was dependent on its enzymatic activity. Mechanistically, ACSS2-induced acetyl-CoA accumulation activated voltage-dependent anion channels 1 transcription through increased H3K27ac occupancy, which subsequently promoted mitophagy and HBV-related HCC tumorigenesis. Notably, targeting ACSS2 by depletion or inhibition with a catalytic inhibitor significantly suppressed tumor growth. Conclusions These findings not only illustrate the interplay between metabolic reprogramming, epigenetic modification, and tumorigenesis in the context of HBV infection, but also highlight ACSS2 as a novel metabolic vulnerability in HBV-related HCC. Therefore, targeting ACSS2 could be a novel strategy against HBV-related HCC.

ObjectiveThe present study aimed to investigate alterations in white matter microstructure and spontaneous neural activity in male college smokers, and to further explore their associations with nicotine dependence. Given that adolescence and early adulthood represent critical periods for brain maturation, particularly for white matter development, understanding the neural correlates of smoking behavior during this stage is of substantial importance for both neuroscience and public health. MethodsA total of 115 male undergraduate students were initially recruited for this study. After quality control and exclusion procedures, 52 male college smokers and 42 demographically matched healthy non-smokers were included in the final analysis. All participants underwent multimodal magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI). White matter fiber tracts were reconstructed using the automated fiber quantification (AFQ) method, which enables precise identification and quantification of major fiber bundles. Eighteen major white matter tracts were segmented for each participant. Along the core trajectory of each tract, 100 equidistant nodes were sampled. Fractional anisotropy (FA) was calculated at each node to assess white matter microstructural integrity, while amplitude of low-frequency fluctuation (ALFF) was computed to evaluate spontaneous neural activity within white matter tracts. Between-group differences in FA and ALFF were assessed using two-sample t-tests, with appropriate corrections applied for multiple comparisons. Furthermore, Pearson correlation analyses were conducted to examine the relationships between imaging-derived metrics (FA and ALFF values in regions showing significant group differences) and nicotine dependence severity, as measured by the Fagerström test for nicotine dependence (FTND). ResultsCompared with healthy non-smokers, male college smokers exhibited significantly increased FA values in several white matter tracts, including the left thalamic radiation, right corticospinal tract, forceps major of the corpus callosum, left uncinate fasciculus, and right arcuate fasciculus. These findings suggest altered microstructural organization or increased directional coherence within these pathways. In addition, smokers demonstrated significantly elevated ALFF values in the forceps major, right uncinate fasciculus, and left arcuate fasciculus, indicating enhanced spontaneous neural activity in these white matter regions. Correlation analyses revealed that FA values in the left thalamic radiation and right corticospinal tract were negatively correlated with FTND scores, suggesting that higher levels of nicotine dependence were associated with reduced microstructural integrity or altered fiber organization in these regions. In contrast, ALFF values in the forceps major and right uncinate fasciculus were positively correlated with FTND scores, indicating that greater nicotine dependence was associated with increased spontaneous neural activity in specific white matter pathways. ConclusionThe present study provides evidence that male college smokers exhibit distinct alterations in both white matter microstructure and functional activity. These abnormalities are not uniformly distributed but rather localized to specific fiber tracts implicated in sensorimotor processing, interhemispheric communication, and higher-order cognitive and emotional regulation. Importantly, the observed associations between imaging metrics and nicotine dependence severity suggest that these structural and functional alterations may reflect neurobiological mechanisms underlying addiction. The combination of AFQ-based tract profiling and multimodal MRI offers a sensitive approach for detecting subtle changes along white matter pathways, highlighting its potential utility in identifying neuroimaging biomarkers of nicotine dependence. Overall, these findings indicate that smoking during early adulthood may disrupt ongoing white matter maturation, potentially leading to long-term consequences for brain function. This study provides novel insights into the neural basis of nicotine dependence and underscores the importance of early intervention and prevention strategies targeting young smokers.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

AIM To investigate the effects of Qifu Yixin Granules on cardiac inflammation in a rat model of heart failure.METHODS The rats were induced into chronic heart failure(CHF)models by 6-week intraperitoneal injection of doxorubicin followed by the random assignment of the successful rat models into the model group,the captopril group(22.5 mg/kg),and the low-dose,medium-dose,and high-dose Qifu Yixin Granules groups(2.84,5.67,11.34 g/kg),in contrast to the normal rats of the blank group.The rats had their body weight monitored;their cardiac function assessed by echocardiography;their serum levels of NT-proBNP,TNF-α,IL-6,IL-1 and CRP measured by ELISA;their cardiac morphological alterations observed by HE and Masson staining;their cardiac protein expressions of TLR4,MyD88 and NF-κB detected by immunohistochemistry and Western blot;and their cardiac mRNA expressions of TLR4,MyD88 and NF-κB measured by RT-qPCR.RESULTS Compared to the blank group,the model group exhibited significantly reduced body weight,LVEF and LVFS(P＜0.01),alongside significantly elevated LVEDD,LVESD,and serum concentrations of NT-proBNP,TNF-α,IL-6,IL-1 and CRP(P＜0.01).Additionally,the model group displayed greater myocardial inflammatory cell aggregation,increased collagen deposition(P＜0.01);and upregulated myocardial protein and mRNA expressions of TLR4,MyD88 and NF-κB(P＜0.01).Compared to the model group,the groups intervened with captopril or medium/high dose Qifu Yixin Granules demonstrated significantly increased body weight,LVEF and LVFS(P＜0.05,P＜0.01);significantly reduced LVEDD,LVESD,and serum levels of the aforementioned indicators(P＜0.05,P＜0.01);mitigated inflammation and collagen deposition(P＜0.05,P＜0.01);and downregulated myocardial protein and mRNA expressions of TLR4,MyD88 and NF-κB(P＜0.05,P＜0.01).CONCLUSION Qifu Yixin Granules attenuate cardiac inflammation and improve cardiac function in doxorubicin-induced CHF rats;this therapeutic effect is mediated by inhibiting the activation of the TLR4/MyD88/NF-κB signaling pathway.

OBJECTIVE: To investigate the accuracy and safety of pedicle screw placement using 3D-printed auxiliary guides in scoliosis correction surgery for adolescents. METHODS: A retrospective analysis was conducted on the clinical data of 51 patients who underwent posterior scoliosis correction surgery from January 2020 to March 2023. Among them, there were 35 cases of adolescent idiopathic scoliosis and 16 cases of congenital scoliosis. The patients were divided into two groups based on the auxiliary tool used:the 3D-printed auxiliary guide screw placement group (3D printing group) and the free-hand screw placement group (free-hand group, without auxiliary tools). The 3D printing group included 32 patients (12 males and 20 females) with an average age of (12.59±2.60) years;the free-hand group included 19 patients (7 males and 12 females) with an average age of (14.58±3.53) years. The two groups were compared in terms of screw placement accuracy and safety, spinal correction rate, intraoperative blood loss, number of intraoperative fluoroscopies, operation time, hospital stay, and preoperative and last follow-up scores of the Scoliosis Research Society-22 (SRS-22) questionnaire. RESULTS: A total of 707 pedicle screws were placed in the two groups, with 441 screws in the 3D printing group and 266 screws in the free-hand group. All patients in both groups successfully completed the surgery. There was a statistically significant difference in operation time between the two groups (P<0.05). The screw placement accuracy rate of the 3D printing group was 95.46% (421/441), among which the Grade A placement rate was 89.34% (394/441);the screw placement accuracy rate of the free-hand group was 86.47% (230/266), with a Grade A placement rate of 73.31% (195/266). There were statistically significant differences in the accuracy of Grade A, B, and C screw placements between the two groups (P<0.05), while no statistically significant differences were observed in intraoperative blood loss, number of fluoroscopies, correction rate, or hospital stay (P>0.05). In the SRS-22 questionnaire scores, the scores of functional status and activity ability, self-image, mental status, and pain of patients in each group at the last follow-up were significantly improved compared with those before surgery (P<0.05), but there were no statistically significant differences in all scores between the two groups (P>0.05). CONCLUSION In scoliosis correction surgery, compared with traditional free-hand screw placement, the use of 3D-printed auxiliary guides for screw placement significantly improves the accuracy and safety of screw placement and shortens the operation time.
Humans ; Male ; Scoliosis/surgery* ; Female ; Adolescent ; Printing, Three-Dimensional ; Retrospective Studies ; Pedicle Screws ; Child

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

Dopamine(DA)is an essential neurotransmitter.Research on its dynamic concentration fluctuations,particularly within the extracellular microenvironment,is crucial for elucidating neural signaling mechanisms and pathogenesis of related disorders.Among DA detection methods,fluorescence probe-based imaging offers advantages such as high sensitivity,high specificity,and non-invasiveness.However,the application of these probes for in situ DA monitoring has been limited by the challenges including probe internalization and difficulties in labeling across cells.Here,leveraging the programmability and high stability of DNA nanostructures,a DNA prism-based probe for imaging DA release at the single-cell level was designed and constructed.This probe utilized surface-modified cholesterol for efficient membrane anchoring and a DA aptamer-based"turn-on"sensing module to detect DA directly on the cell membrane.Using this probe,rapid DA release triggered by high K+stimulation was observed,with the released DA concentration increasing over time and peaking at 8 min post-stimulation.More notably,exploiting the probe's ability to simultaneously anchor to two cells,thereby forming cell clusters,revealed that the distribution of DA within the intercellular space was significantly higher than that in the cell body regions.This probe not only provided a method for DA imaging on the cell membrane but also laid a theoretical foundation for developing broader neurotransmitter detection platforms,holding significant scientific merit and application potential.

Objective:To explore the key components and mechanism of Qufeng Ningfei Powder in treating asthma through qualitative analysis of its blood components, combined with network pharmacology and molecular docking techniques.Methods:The blood components of Qufeng Ningfei Powder were qualitatively analyzed using UPLC-QE-Orbitrap-MS technology. R language was employed to analyze chip data from the GEO database, obtaining a list of differentially expressed genes. SwissTargetPrediction was utilized to predict the targets of drug components. Asthma-related targets were searched through databases such as OMIM, GeneCards, and TTD. The intersection of drug and disease targets was identified using Venn online analysis tool, constructing a "drug-component-target-disease" network to screen potential core components. A protein-protein interaction network (PPI) of core targets was constructed using STRING platform and Cytoscape software. GO function enrichment and KEGG pathway analysis were conducted using DAVID database to validate potential mechanism. Molecular docking was performed to verify the interaction between key components and core targets.Results:A total of 64 components were identified, from which 53 active components were screened, corresponding to 609 targets. Further searching disease databases revealed 96 target genes related to asthma, with an intersection of 6 genes between drug and asthma differential genes. Core target gene IL6 and its corresponding core compound were determined through network topology analysis. Molecular docking confirmed the binding of the main active components of Qufeng Ningfei Powder with the core target protein IL6.Conclusion:The blood components of Qufeng Ningfei Powder may regulate IL-17 through IL6, counteract airway remodeling, oxidative stress, and airway hyperresponsiveness, and thus treat asthma.

OBJECTIVE: To determine the prevalence of lumbar spondylolysis (LS) and the proportion of spondylolytic spondylolisthesis (SS) in China, and to evaluate the musculoskeletal status of patients with LS and SS. METHODS: Spine Computed Tomography (CT) images were collected from community populations aged 40 and above in a nationwide multi-center project. LS was diagnosed, and SS was graded by an experienced radiologist. Bone mineral density (BMD) and paraspinal muscle parameters were quantified based on CT images. RESULTS: One hundred and seventeen patients of a total of 3,317 individuals were diagnosed with LS, corresponding to a prevalence rate of 3.53%. 63 of the 1,214 males (5.18%) and 54 of the 2,103 females (2.57%) were diagnosed with LS. SS occurred in 64/121 vertebrae (52.89%). BMD was not associated with LS ( P = 0.341). The L5 extensor paraspinal muscle density was higher in the LS group than in the non-LS group. In the LS group, patients with SS had a smaller L5 paraspinal extensor muscle cross-sectional area than those without SS ( P = 0.003). CONCLUSION The prevalence of LS in Chinese adults was 3.53%, with prevalence rates of 5.18% in males and 2.57% in females. Patients with LS have higher muscle density, whereas those with SS have smaller muscle cross-sectional areas at the L5 level.
Humans ; Male ; Female ; Middle Aged ; China/epidemiology* ; Prevalence ; Adult ; Lumbar Vertebrae/diagnostic imaging* ; Spondylolysis/diagnostic imaging* ; Aged ; Bone Density ; Tomography, X-Ray Computed ; Aged, 80 and over ; Spondylolisthesis/epidemiology* ; East Asian People